Andrés Rodríguez-Galván

Adsorption and Self-Assembly of Anticancer Antibiotic Doxorubicin on Single-Walled Carbon Nanotubes

We performed a combined experimental and theoretical study of the conjugates obtained from single-walled carbon nanotubes and anticancer antibiotic doxorubicin (DOX). Atomic force microscopy (AFM) imaging at lower magnification revealed, extended regions of single-walled carbon nanotubes (SWNTS) fully covered with DOX adsorbed molecules, along with some bare parts without the adsorbed drug, thus suggesting that the DOX adsorption is a cooperative process. Ambient atmosphere scanning tunneling microscopy (STM) at higher resolutions found that individual SWNTs-DOX conjugates exhibit a periodic texture, whose most important morphological feature is alternating depressions and protrusions along the nanotube. Based on the images and profiles measured, we suggest that doxorubicin molecules self-assemble on SWNTs sidewall according to a helical pattern, in which their tetracyclic fragments are turned with respect to the nanotube axis by about 50∘. To provide an additional insight into the structure of noncovalent SWNTs-DOX conjugates, we employed density functional theory (DFT) calculations with three long-range corrected functionals: M05-2X, wB97X-D and LCBLYP, of which M05-2X yielded the most realistic results in terms of geometries and energies.

Micromolar Cd2+ affects the growth, hierarchical structure and peptide composition of the biosilica of the freshwater diatom Nitzschia palea (Kutzing) W. Smith

Biosilica from diatoms is formed at ambient conditions under the control of biological and physicochemical processes. The changes in growth and biosilica formation through uptake of different concentrations of Cd2+ by the diatom Nitzschia palea (Kützing) W. Smith was investigated, correlating Cd2+ effects to changes in the biosilica nanostructure and the relative content of the encapsulated biomolecules. Diatom growth rates at different Cd2+ concentrations (as 1, 2, 3, 4, and 5 × 10−1 mg L−1 CdCl2) were studied in order to determine the concentrations at which sublethal effects were visible, allowing the harvest of sufficient diatom cells for further experiments. We found a clear correlation between the Cd2+ concentrations and both the nanostructure of the biosilica and content of encapsulated peptides. Cd2+ induced biosilica deformation was assessed by scanning electron microscopy and attenuated total reflectance‐Fourier Transformed Infrared Spectroscopy (FTIR), revealing that micromorphological changes in frustule features (striae, costae, pores) and nanostructural modifications (structure of the silica and conformation of the encapsulated peptides) occurred at applied Cd2+ concentrations of 2 and 3 × 10−1 mg L−1. In particular the FTIR contribution of peptides decreased at elevated Cd2+ concentrations, whereas shifts in wave number of several relevant organic bonds as C = O stretching (1765 cm−1) and possibly hydrated sulfate (1160, 1110 and 980 cm−1) were assigned. Additional analysis of the amide I band showed a relative increase in β‐sheet structure (1680–1620 cm−1) when Cd2+ concentration increased. Cadmium uptake clearly affected the molecular ordering of the biosilica in Nitzschia palea, most probably by interfering in biological or physicochemical processes involved in diatom biosilicification.

Differential cytotoxicity and internalization of graphene family nanomaterials in myocardial cells

Given the well-known physical properties of graphene oxide (GO), numerous applications for this novel nanomaterial have been recently envisioned to improve the performance of biomedical devices. However, the toxicological assessment of GO, which strongly depends on the used material and the studied cell line, is a fundamental task that needs to be performed prior to its use in biomedical applications. Therefore, the toxicological characterization of GO is still ongoing. This study contributes to this, aiming to synthesize and characterize GO particles and thus investigate their toxic effects in myocardial cells. Herein, GO particles were produced from graphite using the Tour method and subsequent mild reduction was carried out to obtain low-reduced GO (LRGO) particles. A qualitative analysis of the viability, cellular uptake, and internalization of particles was carried out using GO (~54% content of oxygen) and LRGO (~37% content of oxygen) and graphite. GO and LRGO reduce the viability of cardiac cells at IC50 of 652.1±1.2 and 129.4±1.2μg/mL, respectively. This shows that LRGO particles produce a five-fold increase in cytotoxicity when compared to GO. The cell uptake pattern of GO and LRGO particles demonstrated that cardiac cells retain a similar complexity to control cells. Morphological alterations examined with electron microscopy showed that internalization by GO and LRGO-treated cells (100μg/mL) occurred affecting the cell structure. These results suggest that the viability of H9c2 cells can be associated with the surface chemistry of GO and LRGO, as defined by the amount of oxygen functionalities, the number of graphitic domains, and the size of particles. High angle annular dark-field scanning transmission electron microscopy, dynamic light-scattering, Fourier-transform infrared, Raman, and X-ray photoelectron spectroscopies were used to characterize the as-prepared materials.

Computational Simulation of Tumor Surgical Resection Coupled with the Immune System Response to Neoplastic Cells

Numerous mathematical and computational models have arisen to study and predict the effects of diverse therapies against cancer (e.g., chemotherapy, immunotherapy, and even therapies under research with oncolytic viruses) but, unfortunately, few efforts have been directed towards development of tumor resection models, the first therapy against cancer. The model hereby presented was stated upon fundamental assumptions to produce a predictor of the clinical outcomes of patients undergoing a tumor resection. It uses ordinary differential equations validated for predicting the immune system response and the tumor growth in oncologic patients. This model could be further extended to a personalized prognosis predictor and tools for improving therapeutic strategies.